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Glama

quantra_health

Check if the QuantLib pricing engine is live by returning the verbatim response from its /health endpoint.

Instructions

Engine liveness, verbatim from GET /health.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. 'Verbatim from GET /health' usefully signals this is a thin read-only passthrough with no side effects, but it says nothing about the failure/healthy distinction, auth requirements, or latency/rate behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded clause with zero filler; the identity of the tool and its data source are in the first few words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter liveness probe with an output schema already defining the return shape, the description is nearly sufficient. The only missing piece is how to interpret an unhealthy result or whether any auth/session context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to clarify beyond the schema; baseline 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and intent: engine liveness, plus the underlying GET /health endpoint. An agent can tell it apart from pricing/build siblings, though there is no explicit contrast drawn with the nearby meta/endpoint tools (quantra_meta, list_endpoints, engine_schema).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use statement, no mention of prerequisites (auth, sessions) and no alternative named. Usage is only inferable from the word 'liveness'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.